Morrison/Long: Tunnels and sequencing: applications on the field

From Kate Morrison and Jeff Long at Baseball Prospectus on September 18, 2017:

When Baseball Prospectus released our pitch tunnels data back in January, we were honest about the realities around the data. At the time, we had some idea of how the data could be used to analyze pitchers, but we certainly didn’t have it all figured out. Of course, while it’s valuable to have new tools through which we can analyze and grow our understanding of the game, we hoped that our pitch tunnels data would prove to be more.

Recently, we added some batted ball outcomes to the data on the stats pages of BP, allowing you to not only see how a pitcher’s pitches look in flight, but to also see what that means in terms of batted ball outcomes. This is, we believe, a big step in being able to better determine the impact that something like pitch tunnels might have on the field. We were thrilled to see what might come out of groups using the data at the SABR analytics conference this spring, and some of the work was truly remarkable.

One of the participants, Scott Spencer from Columbia University, took things a step further and put together a terrific analysis of the impact of pitch tunnels on whiff rates. Spencer has helped us bridge the gap between analysis and on-field application, as his work suggests that pitch tunnels impact whiff rates greatly. His conclusion, seen below, would seem to agree with some of the initial work that Jonathan Judge assisted with when we rolled out pitch tunnels.

Read the full article here:

Originally published: September 18, 2017. Last Updated: September 18, 2017.